Calibration Method Based on the Image of the Absolute Quadratic Curve
| Autor: | Sentang Wu, Wenlei Liu, Xiaolong Wu, Hongbo Zhao |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
Coordinate system Normalization (image processing) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION vanishing point 02 engineering and technology 01 natural sciences Camera calibration fundamental matrix cross ratio invariance 0202 electrical engineering electronic engineering information engineering vanishing line General Materials Science Vanishing point Fundamental matrix (computer vision) Mathematics image of the absolute quadratic curve (IAC) 010401 analytical chemistry General Engineering Quadratic function Rotation matrix 0104 chemical sciences Nonlinear distortion 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering Algorithm lcsh:TK1-9971 Camera resectioning |
| Zdroj: | IEEE Access, Vol 7, Pp 29856-29868 (2019) |
| ISSN: | 2169-3536 |
| Popis: | In this paper, a new camera calibration method based on the image of the absolute quadratic curve (IAC) is proposed, and a new target is designed for this method, which is both convenient and flexible. It first extracts the characteristic points and the characteristic lines of the target and finds out the vanishing point and the vanishing line. The radial and tangential distortion coefficients are obtained by using the cross ratio invariance to correct the target image distortion. Then, the four internal parameters of the camera are obtained by IAC. The influence of the skew parameters is ignored. The rotation matrix is then calculated by the orthogonal characteristic of the coordinate system, and the translation vector is calculated by the center coordinates of the camera. In this way, the internal and external parameters of the camera can be obtained. The internal and external parameters are taken as initial values, and the optimal results are obtained by nonlinear optimization using the reprojection method. Finally, the relative position between different target images can be obtained by using the fundamental matrix, namely, the rotation angle. In the process of solving, the normalization method is used to improve the accuracy of data processing. Not requiring any prior information of the camera, the method has a wide range of applications. |
| Databáze: | OpenAIRE |
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